"Ensemble Machine Learning for Personalized Antihypertensive Treatment."

Bertsimas, Dimitris, Alison Rose Ann Borenstein, Antonin Dauvin, and Agni Orfanoudaki. Naval Research Logistics Vol. 69, No. 5 (2022): 669-688.

"Data-driven Interpretable Policy Construction for Personalized Mobile Health."

Dimitris Bertsimas, Predrag Klasnja, Susan Murphy, and Liangyuan Na. In 2022 IEEE International Conference on Digital Health (ICDH), Barcelona, Spain: July 2022.

"Online Mixed-Integer Optimization in Milliseconds."

Bertsimas, Dimitris, and Bartolomeo Stellato. INFORMS Journal on Computing Vol. 34, No. 4 (2022): 2229-2248. Download Preprint at arXiv.

"POTTER-ICU: An Artificial Intelligence Smartphone-accessible Tool to Predict the Need for Intensive Care After Emergency Surgery."

Gebran, Anthony, Annita Vapsi, Lydia R. Maurer, Mohamad El Moheb, Leon Naar, Sumiran S. Thakur, Robert Sinyard, Dania Daye, George C. Velmahos, Dimitris Bertsimas, and Haytham M A Kaafarani. Surgery Vol. 172, No. 1 (2022): 470-475.

"Hurricane Forecasting: A Novel Multimodal Machine Learning Framework."

Boussioux, Léonard, Cynthia Zeng, Théo Guénais, and Dimitris Bertsimas. Weather and Forecasting Vol. 37, No. 6 (2022): 817-831.

"Machine Learning Reimagined: The Promise of Interpretability to Combat Bias."

Maurer, Lydia R., Dimitris Bertsimas, and Haytham Kaafarani. Annals of Surgery Vol. 275, No. 6 (2022): e738-e739.